It's not obvious, but you can use imwarp() instead of circshift. See this demo:
% Shifts / translates an image to the right by 500 pixels and down by 200 pixels. % Area shifted in is black. clc; % Clear the command window. close all; % Close all figures (except those of imtool.) clear; % Erase all existing variables. Or clearvars if you want. workspace; % Make sure the workspace panel is showing. format long g; format compact; fontSize = 20; grayImage = imread('concordorthophoto.png'); [rows, columns, numberOfColorChannels] = size(grayImage); subplot(1, 2, 1); imshow(grayImage); axis on; title('Original Image', 'fontSize', fontSize); % Enlarge figure to full screen. set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]); deltaX = 500; % Shift x by 500 pixels. deltaY = 200; % Shift y by 200 pixels. D = zeros(rows, columns, 2); D(:,:,1) = -deltaX; % Shift x by 500 pixels. D(:,:,2) = -deltaY; % Shift x by 200 pixels. warpedImage = imwarp(grayImage, D); subplot(1, 2, 2); imshow(warpedImage); axis on; title('Shifted Image', 'fontSize', fontSize);
So just mask the image in place (see demo script freehand_masking_demo.m), then do the shifting with imwarp().
% Demo to have the user freehand draw an irregular shape over a gray scale image. % Then it creates new images: % (1) where the drawn region is all white inside the region and untouched outside the region, % (2) where the drawn region is all black inside the region and untouched outside the region, % (3) where the drawn region is untouched inside the region and all black outside the region. % It also (4) calculates the mean intensity value and standard deviation of the image within that shape, % (5) calculates the perimeter, centroid, and center of mass (weighted centroid), and % (6) crops the drawn region to a new, smaller separate image. % Change the current folder to the folder of this m-file. if(~isdeployed) cd(fileparts(which(mfilename))); end clc; % Clear command window. clear; % Delete all variables. close all; % Close all figure windows except those created by imtool. imtool close all; % Close all figure windows created by imtool. workspace; % Make sure the workspace panel is showing. fontSize = 16; % Read in a standard MATLAB gray scale demo image. folder = fullfile(matlabroot, '\toolbox\images\imdemos'); baseFileName = 'cameraman.tif'; % Get the full filename, with path prepended. fullFileName = fullfile(folder, baseFileName); % Check if file exists. if ~exist(fullFileName, 'file') % File doesn't exist -- didn't find it there. Check the search path for it. fullFileName = baseFileName; % No path this time. if ~exist(fullFileName, 'file') % Still didn't find it. Alert user. errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; end end grayImage = imread(fullFileName); imshow(grayImage, []); axis on; title('Original Grayscale Image', 'FontSize', fontSize); set(gcf, 'Position', get(0,'Screensize')); % Maximize figure. % Ask user to draw freehand mask. message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish'); uiwait(msgbox(message)); hFH = imfreehand(); % Actual line of code to do the drawing. % Create a binary image ("mask") from the ROI object. binaryImage = hFH.createMask(); xy = hFH.getPosition; % Now make it smaller so we can show more images. subplot(2, 4, 1); imshow(grayImage, []); axis on; drawnow; title('Original gray scale image', 'FontSize', fontSize); % Display the freehand mask. subplot(2, 4, 2); imshow(binaryImage); axis on; title('Binary mask of the region', 'FontSize', fontSize); % Label the binary image and computer the centroid and center of mass. labeledImage = bwlabel(binaryImage); measurements = regionprops(binaryImage, grayImage, ... 'area', 'Centroid', 'WeightedCentroid', 'Perimeter'); area = measurements.Area centroid = measurements.Centroid centerOfMass = measurements.WeightedCentroid perimeter = measurements.Perimeter % Calculate the area, in pixels, that they drew. numberOfPixels1 = sum(binaryImage(:)) % Another way to calculate it that takes fractional pixels into account. numberOfPixels2 = bwarea(binaryImage) % Get coordinates of the boundary of the freehand drawn region. structBoundaries = bwboundaries(binaryImage); xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates. x = xy(:, 2); % Columns. y = xy(:, 1); % Rows. subplot(2, 4, 1); % Plot over original image. hold on; % Don't blow away the image. plot(x, y, 'LineWidth', 2); drawnow; % Force it to draw immediately. % Burn region as white into image by setting it to 255 wherever the mask is true. burnedImage = grayImage; burnedImage(binaryImage) = 255; % Display the image with the mask "burned in." subplot(2, 4, 3); imshow(burnedImage); axis on; caption = sprintf('Masked white inside region'); title(caption, 'FontSize', fontSize); % Burn region as black into image by setting it to 255 wherever the mask is true. burnedImage = grayImage; burnedImage(binaryImage) = 0; % Display the image with the mask "burned in." subplot(2, 4, 4); imshow(burnedImage); axis on; caption = sprintf('Masked black inside region'); title(caption, 'FontSize', fontSize); % Mask the image white outside the mask, and display it. % Will keep only the part of the image that's inside the mask, white outside mask. whiteMaskedImage = grayImage; whiteMaskedImage(~binaryImage) = 255; subplot(2, 4, 5); imshow(whiteMaskedImage); axis on; title('Masked white outside region', 'FontSize', fontSize); % Mask the image outside the mask, and display it. % Will keep only the part of the image that's inside the mask, zero outside mask. blackMaskedImage = grayImage; blackMaskedImage(~binaryImage) = 0; subplot(2, 4, 6); imshow(blackMaskedImage); axis on; title('Masked black outside region', 'FontSize', fontSize); % Calculate the mean meanGL = mean(blackMaskedImage(binaryImage)); sdGL = std(double(blackMaskedImage(binaryImage))); % Put up crosses at the centriod and center of mass hold on; plot(centroid(1), centroid(2), 'r+', 'MarkerSize', 30, 'LineWidth', 2); plot(centerOfMass(1), centerOfMass(2), 'g+', 'MarkerSize', 20, 'LineWidth', 2); % Now crop the image. leftColumn = min(x); rightColumn = max(x); topLine = min(y); bottomLine = max(y); width = rightColumn - leftColumn + 1; height = bottomLine - topLine + 1; croppedImage = imcrop(blackMaskedImage, [leftColumn, topLine, width, height]); % Display cropped image. subplot(2, 4, 7:8); imshow(croppedImage); axis on; title('Cropped image', 'FontSize', fontSize); % Put up crosses at the centriod and center of mass hold on; plot(centroid(1)-leftColumn, centroid(2)-topLine, 'r+', 'MarkerSize', 30, 'LineWidth', 2); plot(centerOfMass(1)-leftColumn, centerOfMass(2)-topLine, 'g+', 'MarkerSize', 20, 'LineWidth', 2); % Report results. message = sprintf('Mean value within drawn area = %.3f\nStandard deviation within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f\nperimeter = %.2f\nCentroid at (x,y) = (%.1f, %.1f)\nCenter of Mass at (x,y) = (%.1f, %.1f)\nRed crosshairs at centroid.\nGreen crosshairs at center of mass.', ... meanGL, sdGL, numberOfPixels1, numberOfPixels2, perimeter, ... centroid(1), centroid(2), centerOfMass(1), centerOfMass(2)); msgbox(message);
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